• Title/Summary/Keyword: Noise Image

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Development of Rotation Invariant Real-Time Multiple Face-Detection Engine (회전변화에 무관한 실시간 다중 얼굴 검출 엔진 개발)

  • Han, Dong-Il;Choi, Jong-Ho;Yoo, Seong-Joon;Oh, Se-Chang;Cho, Jae-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.116-128
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    • 2011
  • In this paper, we propose the structure of a high-performance face-detection engine that responds well to facial rotating changes using rotation transformation which minimize the required memory usage compared to the previous face-detection engine. The validity of the proposed structure has been verified through the implementation of FPGA. For high performance face detection, the MCT (Modified Census Transform) method, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. And the rotation transformation method was added to maintain effectiveness against face rotating changes. The proposed hardware structure was composed of Color Space Converter, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT(Modified Census Transform), Candidate Detector / Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor / Color Overlay Processor. The face detection engine was tested using a Virtex5 LX330 FPGA board, a QVGA grade CMOS camera, and an LCD Display. It was verified that the engine demonstrated excellent performance in diverse real life environments and in a face detection standard database. As a result, a high performance real time face detection engine that can conduct real time processing at speeds of at least 60 frames per second, which is effective against lighting changes and face rotating changes and can detect 32 faces in diverse sizes simultaneously, was developed.

Efficient Structure-Oriented Filter-Edge Preserving (SOF-EP) Method using the Corner Response (모서리 반응을 이용한 효과적인 Structure-Oriented Filter-Edge Preserving (SOF-EP) 기법)

  • Kim, Bona;Byun, Joongmoo;Seol, Soon Jee
    • Geophysics and Geophysical Exploration
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    • v.20 no.3
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    • pp.176-184
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    • 2017
  • To interpret the seismic image precisely, random noises should be suppressed and the continuity of the image should be enhanced by using the appropriate smoothing techniques. Structure-Oriented Filter-Edge Preserving (SOF-EP) technique is one of the methods, that have been actively researched and used until now, to efficiently smooth seismic data while preserving the continuity of signal. This technique is based on the principle that diffusion occurs from large amplitude to small one. In a continuous structure such as a horizontal layer, diffusion or smoothing is operated along the layer, thereby increasing the continuity of layers and eliminating random noise. In addition, diffusion or smoothing across boundaries at discontinuous structures such as faults can be avoided by employing the continuity decision factor. Accordingly, the precision of the smoothing technique can be improved. However, in the case of the structure-oriented semblance technique, which has been used to calculate the continuity factor, it takes lots of time depending on the size of the filter and data. In this study, we first implemented the SOF-EP method and confirmed its effectiveness by applying it step by step to the field data. Next, we proposed and applied the corner response method which can efficiently calculate the continuity decision factor instead of structure-oriented semblance. As a result, we could confirm that the computation time can be reduced by about 6,000 times or more by applying the corner response method.

Ship Detection Based on KOMPSAT-5 SLC Image and AIS Data (KOMPSAT-5 SLC 영상과 AIS 데이터에 기반한 선박탐지)

  • Kim, Donghan;Lee, Yoon-Kyung;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.365-377
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    • 2020
  • Continuous monitoring and immediate response is essential to protect the national maritime territory and maritime resources from the activities of illegal ships. Synthetic Aperture Radar (SAR) images with a wide range of images are effective for maritime surveillance asthe weather and day-night conditions rarely affect to image acquisition. However, an effective ship detection is not easy due to the huge data size of SAR images and various characteristics such as the speckle noise. In this study, the Human Visual Attention System (HVAS) algorithm was applied to KOMPSAT-5 to extract the initial targets, and the SAR-Split algorithm depending on the imaging modes was used to remove false alarms. The detected targets were finally selected by the Constant False Alarm Rate (CFAR) algorithm and matched with the ship's Automatic Identification System (AIS) information. Overall, the detected targets were well matched with AIS data, but some false alarms by ship wakes were observed. The detection rate was about 80% in ES mode and about 64% in ST mode. It is expected that the developed ship detection algorithm will contribute to the construction of a wide area maritime surveillance network.

Eyelid Detection Algorithm Based on Parabolic Hough Transform for Iris Recognition (홍채 인식을 위한 포물 허프 변환 기반 눈꺼풀 영역 검출 알고리즘)

  • Jang, Young-Kyoon;Kang, Byung-Jun;Park, Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.1
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    • pp.94-104
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    • 2007
  • Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.

Development of Solenoid RF Coil for Animal Imaging in 3T High Magnetic Field MRI (고자장 3T MRI 장비에서 동물영상을 위한 솔레노이드 RF코일 개발)

  • Lee, Hong-Seok;Woo, Dong-Cheol;Min, Kwang-Hong;Kim, Yong-Kwon;Lee, Heung-Kyu;Choe, Bo-Young
    • Investigative Magnetic Resonance Imaging
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    • v.11 no.1
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    • pp.20-26
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    • 2007
  • Purpose : The purpose of the present study was to develop and optimize solenoid coil for animal- model in 3 T MRI system and investigate and compare with the birdcage coil concerning the image quality with the various parameters such as SNR and Q-factor. Materials and Methods : Solenoid coil for animal-model was made on the acryl structure (diameter 4 cm, length 10 cm) 3 times-winding cooper tape of width 2 cm, thickness 0.05 cm and length 10 cm with 2 cm interval between winded tapes. Capacitors from 2 pF to 100 pF were used, and the solenoid coil was designed for receiver only coil. Results : SNR of the developed solenoid was 985 in CuSO4 0.7 g/L and 995 in rat experiment. Q-factor was 84-89 in unloaded condition and 203-206 in loaded condition. Conclusion : The resolution of the image obtained from solenoid was relatively higher than that of the conventional birdcage coil. In addition, the homogeneity of RF field by coil simulation was significantly excellent. The present study demonstrated that the solenoid coil could be useful to obtain small animal images with better contrast, resolution, visibility than images from birdcage.

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Turbo FLASH NRI Using Optimized Flip Angle Pattern: Application to Inversion-Recovery T1-Weighted Imaging (최적화된 Flip Angle Pattern을 사용한 Turbo FLASH MRI: Inversion-Recovery T1-Weighted Imaging에의 응용)

  • Oh, C.H.;Choi, H.J.;Yang, Y.J.;Lee, D.R.;Ryu, Y.C.;Hyun, J.H.;Kim, S.R.;Yi, Y.;Jung, K.J.;Ahn, C.B.
    • Proceedings of the KOSOMBE Conference
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    • v.1998 no.11
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    • pp.55-56
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    • 1998
  • The 3-D Fast Gradient Echo (Turbo FLASH, Turbo Fast Low Angle Shot) sequence is optimized to achieve a good T1 contrast using variable excitation flip angles. In Turbo FLASH sequence, depending on the contrast preparation scheme, various types of image contrast can be established. While proton density contrast is obtained when using a short repetition time with a short echo time and small flip angles, T1 or T2 weighting can be obtained with proper contrast preparation sequences applied before the above proton density Turbo FLASH sequence. To maximize the contrast to noise ratio while retaining a sharp impulse response (smooth frequency domain response), the excitation flip-angle pattern is optimized through simulation and experiments. The TI (the delay after the preparation sequence which is a 180 degree inversion RF pulse in the IR T1 weighted imaging case), TD (the delay time between the Turbo FLASH sequence and the next preparation), and TR are also optimized fur the best image quality. The proposed 3-D Turbo FLASH provides $1mm\times1mm\times1.5mm$ high resolution images within a reasonable 5-8 minutes of imaging time. The proposed imaging sequence has been implemented in a Medison's Magnum 1.0T system and verified through simulations as well as human volunteer imaging. The experimental results show the utility of the proposed method.

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Material Decomposition through Weighted Image Subtraction in Dual-energy Spectral Mammography with an Energy-resolved Photon-counting Detector using Monte Carlo Simulation (몬테카를로 시뮬레이션을 이용한 광자계수검출기 기반 이중에너지 스펙트럼 유방촬영에서 가중 영상 감산법을 통한 물질분리)

  • Eom, Jisoo;Kang, Sooncheol;Lee, Seungwan
    • Journal of radiological science and technology
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    • v.40 no.3
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    • pp.443-451
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    • 2017
  • Mammography is commonly used for screening early breast cancer. However, mammographic images, which depend on the physical properties of breast components, are limited to provide information about whether a lesion is malignant or benign. Although a dual-energy subtraction technique decomposes a certain material from a mixture, it increases radiation dose and degrades the accuracy of material decomposition. In this study, we simulated a breast phantom using attenuation characteristics, and we proposed a technique to enable the accurate material decomposition by applying weighting factors for the dual-energy mammography based on a photon-counting detector using a Monte Carlo simulation tool. We also evaluated the contrast and noise of simulated breast images for validating the proposed technique. As a result, the contrast for a malignant tumor in the dual-energy weighted subtraction technique was 0.98 and 1.06 times similar than those in the general mammography and dual-energy subtraction techniques, respectively. However the contrast between malignant and benign tumors dramatically increased 13.54 times due to the low contrast of a benign tumor. Therefore, the proposed technique can increase the material decomposition accuracy for malignant tumor and improve the diagnostic accuracy of mammography.

Development of Quantification Method for Bioluminescence Imaging (발광영상에 대한 정량화 방법 개발)

  • Kim, Hyeon-Sik;Choi, Eun-Seo;Tak, Yoon-O;Choi, Heung-Kook;Lee, Ju-Young;Min, Jung-Joon;Lee, Byeong-Il
    • Nuclear Medicine and Molecular Imaging
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    • v.43 no.5
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    • pp.451-458
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    • 2009
  • Purpose: Optical molecular luminescence imaging is widely used for detection and imaging of bio-photons emitted by luminescent luciferase activation. The measured photons in this method provide the degree of molecular alteration or cell numbers with the advantage of high signal-to-noise ratio. To extract useful information from the measured results, the analysis based on a proper quantification method is necessary. In this research, we propose a quantification method presenting linear response of measured light signal to measurement time. Materials and Methods: We detected the luminescence signal by using lab-made optical imaging equipment of animal light imaging system (ALIS) and different two kinds of light sources. One is three bacterial light-emitting sources containing different number of bacteria. The other is three different non-bacterial light sources emitting very weak light. By using the concept of the candela and the flux, we could derive simplified linear quantification formula. After experimentally measuring light intensity, the data was processed with the proposed quantification function. Results: We could obtain linear response of photon counts to measurement time by applying the pre-determined quantification function. The ratio of the re-calculated photon counts and measurement time present a constant value although different light source was applied. Conclusion: The quantification function for linear response could be applicable to the standard quantification process. The proposed method could be used for the exact quantitative analysis in various light imaging equipments with presenting linear response behavior of constant light emitting sources to measurement time.

Changes in the Number of Matching Points in CCTV's Stereo Images by Indoor/Outdoor Illuminance (실내·외 조도에 따른 스테레오 CCTV 영상 정합점 수 변화)

  • Moon, Kwang Il;Pyeon, Mu Wook;Kim, Jong Hwa;Kim, Kang San
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.1
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    • pp.129-135
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    • 2015
  • The Ubiquitous City (U-City) spatial information technology aimed to provide services freely anytime and anywhere by converging high-tech information & communication technology in urban infrastructure has been available in diverse patterns. In particular, there have been studies on the development of 3D spatial information after selecting and matching key points with stereo images from the many Closed Circuit TV (CCTV) in the U-City. However, the data mostly used in extracting matching points haven't considered external environmental impacts such as illuminance. This study tested how much the matching points needed to construct 3D spatial information with the CCTV whose image quality is dependent upon changes in illuminance fluctuate under the same hardware performances. According to analysis on the number of matching points by illuminance, the number of matching points increased up to 3,000Lux in proportion to the illuminance when IRIS, shutter speed and ISO were fixed. In addition, a border between an object and background became more distinctive. When there was too much light, however, the page became brighter, and noise occurred. Furthermore, it was difficult to name key points because of the collapse of an inter-object border. It appears that if filmed with the study results, the number of matching points would increase.

A Study on Detection of Deforested Land Using Aerial Photographs (항공사진을 이용한 훼손 산지 탐지 연구)

  • Ham, Bo Young;Lee, Chun Yong;Byun, Hye Kyung;Min, Byoung Keol
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.11-17
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    • 2013
  • With high social demands for the diverse utilizations of forest lands, the illegal forest land use changes have increased. We studied change detection technique to detect changes in forest land use using an object-oriented segmentation of RED bands differencing in multi-temporal aerial photographs. The new object-oriented segmentation method consists of the 5 steps, "Image Composite - Segmentation - Reshaping - Noise Remover - Change Detection". The method enabled extraction of deforested objects by selecting a suitable threshold to determine whether the objects was divided or merged, based on the relations between the objects, spectral characteristics and contextual information from multi-temporal aerial photographs. The results found that the object-oriented segmentation method detected 12% of changes in forest land use, with 96% of the average detection accuracy compared by visual interpretation. Therefore this research showed that the spatial data by the object-oriented segmentation method can be complementary to the one by a visual interpretation method, and proved the possibility of automatically detecting and extracting changes in forest land use from multi-temporal aerial photographs.